Uses of Satellite Data for Monitoring and Forecasts of Hurricane and Coastal Precipitation

Fuzhong Weng NOAA/NESDIS/Center for Satellite Applications and Research

Xiaolei Zou

Florida State University

Vijay Tallapragada and Andrew Collard NOAA/NWS/Environmental Modeling Center

And

STAR/EMC Satellite Data Assimilation Team Members (Ben Zhang, Lin Lin, In-Hyuk Kwon, and Haixia Liu)

Impacts of Satellite Data on Global Medium-Range Weather Forecasts

0 2 4 6 8 10 12 14 16 18

O3: Ozone from satellites METEOSAT IR Rad (T,H)

MTSATIMG: Japanese geostationary sat vis and IR imagery GOES IR rad (T,H)

MODIS: Moderate Resolution Imaging Spectroradiometer (winds) GMS: Japanese geostationary satellite winds

SSMI: Special Sensor MW Imager (H and sfc winds) AMSRE: MW imager radiances (clouds and precip)

MHS: MW humidity sounder on NOAA POES and METOP (H) MSG: METEOSAT 2nd Generation IR rad (T,H)

HIRS: High-Resol IR Sounder on NOAA POES (T,H) PILOT: Pilot balloons and wind profilers (winds)

Ocean buoys (Sfc P, H and winds) METEOSAT winds

GOES winds AMSU-B: Adv MW Sounder B on NOAA POES

SYNOP: Sfc P over land and oceans,H, and winds over oceans QuikSCAT: sfc winds over oceans

TEMP: Radiosonde T, H, and winds GPSRO: RO bending angles from COSMIC, METOP

AIREP: Aircraft T, H, and winds AIRS: Atmos IR Sounder on Aqua (T,H)

IASI: IR Atmos Interferometer on METOP (T,H) AMSU-A: Adv MW Sounder A on Aqua and NOAA POES (T)

Forecast error reduction contribution (%)

2009 2010 2004 2005 2006 2007 2008 2011 2012 2013 2014 2015 2016 2017 2018

2019 2020

PM Orbit

Mid-AM Orbit

Early-AM Orbit

DMSP 17 DMSP 19

DMSP 20

METOP-B METOP-C

METOP-A

DMSP 16 DMSP 18

NOAA 18

NOAA 19

NPP

JPSS-1

DMSP: SSMI/S

METOP: AVHRR HIRS IASI AMSU-A MHS GOME-2 ASCAT GRAS

NOAA: AVHRR HIRS AMSU-A MHS SBUV/2

NPP: VIIRS, ATMS, OMPS, CrIS

C1:VIIRS, ATMS, OMPS, CrIS

NOAA/METOP/DMSP Satellite System

Suomi NPP Instruments NPP/JPSS Instrument! Measurement !

ATMS - Advanced Technology Microwave Sounder !

ATMS  and  CrIS  together  provide  high  ver4cal  resolu4on  temperature  and  water  vapor  informa.on  needed  to  maintain  and  improve  forecast  skill  out  to  5  to  7  days  in  advance  for  extreme  weather  events,  including  hurricanes  and  severe  weather  outbreaks

CrIS - Cross-track Infrared Sounder !

VIIRS – Visible Infrared Imager Radiometer Suite!

VIIRS  provides  many  cri.cal  imagery  products  including  snow/ice  cover,  clouds,  fog,  aerosols,  fire,  smoke  plumes,  vegeta4on  health,  phytoplankton  abundance/chlorophyll  

OMPS - Ozone Mapping and Profiler Suite!!

 Ozone  spectrometers  for  monitoring  ozone  hole  and  recovery  of  stratospheric  ozone  and  for  UV  index  forecasts  

CERES - Clouds and the Earthʼs Radiant Energy System!!

Scanning radiometer which supports studies of Earth Radiation Budget!

The First ATMS Image at 183GHz

6 1

48

96

 

49

Scan angle Beam width

ATMS Scan Angle and Beam Width

Channel Nadir Resolution (km) Outmost FOV size (km)

ATMS AMSU ATMS AMSU Cross-track Along-track

ATMS AMSU ATMS AMSU

1-2 1-2 74.8 48.6 323.1 155.2 141.8 85.6

3-16 3-15 31.6 48.6 136.7 155.2 60.0 85.6

17-22 16-20 15.8 16.2 68.4 58.9 30.0 29.4

7

Comparison of Spatial Temperature Structure between ATMS and AMSU-A (CH2)

NPP ATMS and VIIRS Imager and Products

Warm Core Cross section along 26.0 N VIIRS 0.64 µm visible and 11.45 µm IR images at 18:33 UTC, 28 Aug 2012

METAR, MSL Pressure, and Buoys information included

Hurricane Sandy Warm Core Anomaly Ascending 1730 UTC, 29 October 2012

Cross section along Longitude 72.9 W Cross section along Latitude 38.1 N

At 1800 UTC Oct 29 Max Wind: 90 MPH, Min Pressure: 940 hPa

Sandy Max Wind, Warm Core and MSLP

The First Light CrIS Image

Spectral Coverage of Thermal Sounders (Example BT’s for AIRS, IASI, & CrIS)

AIRS, 2378 Channels

CrIS 1305

IASI, 8401 Channels

CO2 CO2 O3 CO CH4

13

Example of T(p) & q(p) Channel Kernel Functions

AIRS 15 µm (650-800 cm-1) band

K = dR/dT

AIRS 6.7 µm (1200-1600 cm-1) band

K = dR/dq

14

CrIS Radiometric Calibration: Compared to AIRS and IASI

AIRS

CrIS

CrIS-AIRS

IASI

CrIS

CrIS-IASI

CrIS  has  about  0.2K  warm  bias  wrt  IASI    and  no  bias  wrt  AIRS  from  SNO  collocated  data  sets.  In  the  analysis,  IASI  data  was  de-­‐apodized  to  obtain  the  original  interferogram  data  and  are  then  resampled  using  CrIS  spectrum  resolu4on,  and  FFT  back  to  get  CrIS  like  radiances        

Courtesy of Likun Wang, STAR

CrIS SDR Spectra and Global Coverage

FOV  (~14km  nadir)  FOR  (~50km,  Nadir)  

VSC

Window  Channel   Water  vapor  Channel  

Total  clear  sky  observa4on  points  ~400000  

allFOVFOVi CRTMObsCRTMObsBIASi

)()( −−−=

Blue:  a:er  nonlinearity  coefficient  change  but  before  spectral  coefficient  change  

Black:  before  nonlinearity  and  spectral  coefficient  changes    

Red:  a:er  nonlinearity  coefficient  and  spectral  coefficient  changes    

The  achieved  uniformity  of  the  spectral  and  radiometric  uncertain5es  cross  the  9  FOVs  is  important  for  NWP  to  maximize  the  use  of  the  radiance  data  

CrIS Individual FOV Bias wrt NWP Simulations

Courtesy of Yong Chen, STAR

From Niels Bormann, ECMWF

Forecast Impact of CrIS in ECMWF

Radiance  observa4ons  from  CrIS  have  only  been  available  since  26  June  2012  and  thus  forecast  impact  experiments  are  not  yet  mature.    However,  preliminary  results  suggest  that    assimila4ng  just  57  key  temperature  sounding  channels  from  CrIS  in  addi.on  to    AIRS  and  IASI  can  improve  forecasts  compared  to  the  control.                              Note  that  the  orbit  of  NPP  is  on  top  of  that  of  AQUA  (13:30)  so  CrIS  and  AIRS  data  are  used  in  close  proximity  –  work  con4nues  to  op4mise  analysis  weights.  

Northern  Hemisphere  ,  Z  500  hPa;  2-­‐month  trial  

CrIS  good  

CrIS    bad  

0 1 2 3 4 5 6 Forecast day

0.04

0.02

0.00

-0.02

0.06

MetOp Instruments

•  AVHRR/3 - Advanced Very High Resolution Radiometer

•  HIRS/4 - High Resolution Infrared Sounder

•  AMSU-A - Advanced Microwave Sounding Units-A1/A2

•  MHS - Microwave Humidity Sounder

•  ASCAT - Advanced Scatterometer

•  GOME-2 - Global Ozone Monitoring Experiment-2

•  IASI - Infrared Atmospheric Sounding Interferometer

•  GRAS - The GNSS (Global Navigation Satellite System) Receiver for Atmospheric Sounding (GRAS)

Highlighted instruments in red are the common ones which are also on board of NOAA satellites

Ozone Perturbation during Hurricane Event: An Example of METOP GOME-2

Metop-A Metop-A and Metop-B

GPSRO Measurements: Example Metop-B GRAS

Slide: 20

Metop-B: Validation in October 2012 (against COSMIC)

Radio occultation bending angle co-location statistics of GRAS on Metop-A, -B and COSMIC (within 300km, 3h). Otherwise as previous plot.

Surface Scatterometer Wind: METOP ASCAT L2 Winds

•  ASCAT-A and –B winds very similar •  Top: ASCAT-B in blue •  Left: ASCAT-B statistics for wind speed,

direction and u/v components, with respect to ECMWF winds: wind quality already well within requirements

23

Passive Microwave Imager: an example of GCOM-W1 AMSR-2 Instrument

•  Deployable main reflector system with 2.0m diameter.

•  Frequency channel set is identical to that of AMSR-E except 7.3GHz channel for RFI mitigation.

•  2-point external calibration with the improved HTS (hot-load).

AMSR2 Channel Set Center Freq. [GHz]

Band width [MHz]

Polarization

Beam width [deg] (Ground res. [km])

Sampling interval

[km]

6.925/ 7.3 350

V and H

1.8 (35 x 62)

10

1.7 (34 x 58) 10.65 100 1.2 (24 x 42) 18.7 200 0.65 (14 x 22) 23.8 400 0.75 (15 x 26) 36.5 1000 0.35 (7 x 12) 89.0 3000 0.15 (3 x 5) 5

Stowed

AMSR2 characteristics

Scan Conical scan

Swath width 1450km Antenna 2.0m offset parabola Digitalization 12bit

Incidence angle nominal 55 degree

Polarization Vertical and Horizontal Dynamic range 2.7-340K

Deployed

GCOM-W AMSR-2 provides higher space resolutions compared its precursor on EOS-Aqua (AMSR-E) and better design for mitigating radio frequency interference in land remote sensing application

Information Content from GCOM-W1 AMSR2

Duration 9 - 21 February 2012 MSPD=115 mph MSLP=932 (hPa) JAXA launched GCOM-W1 on Oct 18, 2011 with AMSR2 on board and NESDIS is developing

NOAA unique AMSR2 products for user community.

AMSR-E Ocean Products: Theoretical Base

7095

120145170195220245270

0 1 2 3 4 5 6 7 8 9 10Liquid Water Path (mm)

T H (K

)

10.65 GHz 18.7 GHz 36.5 GHz

(b)

170

185

200

215

230

245

260

275

0 1 2 3 4 5 6 7 8 9 10

Liquid Water Path (mm)

T V (K

)

10.65 GHz 18.7 GHz 36.5 GHz

(a)

155

160

165

170

175

180

185

270 275 280 285 290 295 300 305 310

SST (K)

T V (K

)

6.925 GHz 10.65 GHz

(c)

70

80

90

100

110

120

130

140

0 3 6 9 12 15 18 21 24 27 30

SSW (m/s)

T H (K

)

6.925 GHz 10.65 GHz

(d)

Information Content from GCOM-W1 AMSR2 Hurricane Sandy-10-28-2012 06 UTC

Duration 9 - 21 February 2012 MSPD=115 mph MSLP=932 (hPa)

JAXA launched GCOM-W1 on Oct 18, 2011 with AMSR2 on board and NESDIS is developing NOAA unique AMSR2 products for user community.

SST SSW

Information Content from GCOM-W1 AMSR2 Hurricane Sandy-10-28-2012 06 UTC

Duration 9 - 21 February 2012 MSPD=115 mph MSLP=932 (hPa) JAXA launched GCOM-W1 on Oct 18, 2011 with AMSR2 on board and NESDIS is developing

NOAA unique AMSR2 products for user community.

TPW CLW

Forecasts of Hurricane Sandy without Polar satellites Tony McNally

ECMWF forecasts of Mean Sea Level Pressure, 5 days in advance of the 30th October 2012 for the landfall of Hurricane Sandy. Forecasts from an assimilation system with no polar satellites fail to predict the landfall of the storm on the US east coast.

NO  POLAR  SAT  ECMWF  OPS   VERIFICATION  

5 day forecast: Base time 2012-10-25-00z Valid Time: 2012-10-30-00z

Satellite Data Critical for Improving Hurricane and Coastal Precipitation Forecasts

•  Satellite microwave sounding data – provide hurricane thermal/moisture structure for improving intensity forecast (SSMIS/AMSU-A/MHS/ATMS)

•  Satellite infrared sounding data – provide environmental thermal and moisture structure for track and precipitation forecast (HIRS/CrIS/AIRS/IASI)

•  Ocean surface wind and temperature from satellite scatterometer and passive microwave imager – provide surface energy flux and surface vortex (ASCAT/AMSR2/GMI)

•  GPSRO refractivity and bending angle – provide tropical cyclonegenesis information (COSMIC/GRAS)

•  Geostationary sounder and imager – provide real-time monitoring and tracking of all severe weather events with a high temporal and spatial resolutions (e.g. GOES etc).

Statement of Problems in GSI

•  NCEP GSI (3DVar data assimilation system) is being used by community for both global and regional model analysis but its interface is not designed well for different model configurations

•  In 2011 and 2012 version of Hurricane Weather Research Forecast (HWRF) model, most of satellite data are not used in HWRF analysis process due to its model top setup

•  Analyses show GSI quality controls for satellite water vapor

sounding data are also problematic (lots of bad data sneak into the analysis process).

•  Bias correction schemes for satellite data developed for the global model applications have not been fully vetted for regional model applications

STAR Baseline HWRF Model and Data Assimilation System

HWRF Model:

•  2012 NCEP-Trunk version 934

•  Three telescoping domains: Outer domain: 27km: 75x75o; Inner domain: 9km ~11x10o Inner-most domain: 3km inner-most nest ~6x6o

Revised Model Level and Top:

•  Vertical levels: 61

•  Model top: 0.5 hPa

Data Assimilation System:

•  GFS 6 hour forecasts

•  GSI (3DVAR)

• The Hurricane Weather Research and Forecasting (HWRF) Model dynamical core is designed based on the WRF model using NCEP Non-Hydrostatic Mesoscale Model (NMM) core with a movable high-resolution nested grid (telescopic) • Regional-Scale, Moving Nest, Ocean-Atmosphere Coupled Modeling System. Horizontal resolution: 27 km outer grid, 9 km inner grid, 42 vertical levels • Non-Hydrostaticsystem of equations formulated on a rotated latitude-longitude, Arakawa E-grid and a vertical, pressure hybrid (sigma_p-P) coordinate. • Advanced HWRF 3D Variational analysis that includes vortex relocation, correction to winds, MSLP, temperature and moisture in the hurricane region and adjustment to actual storm intensity. • Uses SAS convection scheme, GFS/GFDL surface, boundary layer physics, GFDL/GFS radiation and Ferrier Microphysical Scheme. • Ocean coupled modeling system (POM/HYCOM).

Data Sets Used for STAR HWRF Assimilation

Conventional Data: Radiosondes, aircraft reports (AIREP/PIREP, RECCO, MDCRS-ACARS, TAMDAR, AMDAR), Surface ship and buoy observations , Surface observations over land, Pibal winds,Wind profilers, VAD wind, Dropsondes

Baseline Satellite Instrument Data:

•  AMSU-A (channel 5-14) from NOAA-18,19 and METOP-A, METOP-B •  HIRS from NOAA-19,METOP-A, METOP-B •  AIRS from EOS Aqua •  IASI from METOP-A and METOP-B •  ASCAT from METOP-A and METOP-B •  GPSRO from GRAS, COSMIC •  CrIS/ATMS from Suomi NPP ( to be added) •  SSMIS from F18 ( to be added) •  AMSR2 from GCOM-W1 ( to be added)

Number of Satellite Data Assimilated in HWRF-L61F

Cycle

2218Z

2306Z 2318Z

2406Z 2418Z

2506Z

2518Z

2606Z

2618Z 2718Z

2806Z

2818Z

2918Z

Dat

a N

umbe

r

0

50000

100000

150000

200000

250000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

AMSU-A (N19)

HIRS4 (N19)

AMSU-A (Metop-A)

AMSU-A (N18)

AIRS (Aqua)

HIRS4 (Metop-A)

0

5000

10000

15000

20000

25000

30000

35000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 0

10000

20000

30000

40000

50000

60000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

0 5000

10000 15000 20000 25000 30000 35000 40000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Cycle Cycle

Cycle

AMSU-A (N18) AMSU-A (N19)

AMSU-A (Metop-A)

Dat

a N

umbe

r

Dat

a N

umbe

r

Dat

a N

umbe

r

Number of Satellite Data Assimilated in HWRF-L61F

0 1000 2000 3000 4000 5000 6000 7000 8000 9000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 0

2000 4000 6000 8000

10000 12000 14000 16000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

0

20000

40000

60000

80000

100000

120000

140000

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Cycle Cycle

Cycle

HIRS4 (Metop-A) HIRS4 (N19)

AIRS (Aqua)

Dat

a N

umbe

r

Dat

a N

umbe

r

Dat

a N

umbe

r

Number of Satellite Data Assimilated in HWRF-L61F

HWRF GFS

Multiple Forecasts of Tracks

L61C L61F

Multiple Forecasts of Tracks

Multiple Forecasts of Max. Wind Speed GFS HWRF

L61F

38

L61C

Multiple Forecasts of Min. Surf. Pres.

GFS HWRF

L61F L61C

Summary and Conclusions

•  NOAA, METOP, DMSP polar satellites provide critical information on atmospheric vertical temperature structure for hurricane monitoring and forecasts

•  Suomi NPP ATMS is very unique for resolving hurricane warm core features through spatial oversampling and additional channel

•  GCOM-W1 AMSR2 are new instrument and can provide surface wind speed and SST for hurricane applications

•  METOP and FY-3 unique instruments ((e.g. GPSRO, scattterometer, ozone) provide more information for NWP and other environmental applications

•  A baseline version of HWRF and satellite instruments is defined for our hurricane and typhoon research and applications.

•  In 2012 hurricane and typhoon season, Our baseline HWRF/DA system in general improves the intensity forecasts for most of study cases including Hurricane Sandy